Evaluation of the climate change impact on the extreme rainfall amounts using modified method of fragments for sub‐daily rainfall disaggregation

Abstract

Climate change has a dramatic effect on the hydrologic variables including extreme rainfall amounts. To evaluate the climate change effects, general circulation models (GCMs) have been developed. However, due to the daily temporal scale of GCM outputs which could be insufficient for some hydrological studies, disaggregation models are introduced. The available disaggregation models which are almost useful in producing time series of finer scale than a day, cannot accurately estimate some statistical characteristics such as extreme events. The method of fragments (MOF) is one of the disaggregation models which considers daily rainfall as the only input. In the present study, in addition to daily rainfall, other influential factors on the rainfall distribution during a day such as weather variables and sub‐daily characteristics have been considered to improve the disaggregation results especially extreme events estimation in the MOF model. The two introduced approaches have been examined for a case study in Tehran, Iran and indicated that weather variables and sub‐daily characteristics are effective in the daily rainfall disaggregation during the dry and wet seasons, respectively. These approaches seem to be much better than the basic MOF in sub‐daily rainfall disaggregation. Hence, the modified disaggregation approaches have been used to evaluate the climate change impacts on the sub‐daily rainfall distribution. The obtained results indicated an increase in the extreme value statistics such as mean and standard deviation of the 95th percentile data compared with the historical ones.

Review: Fractal Geometry in Precipitation

“…Under a theoretical framework, the temporal structure of precipitation can also be simulated from stochastic processes of time-scaling or disaggregation. For instance, the method of fragments is a daily-to-subdaily scaling that employs a nonparametric resampling technique and conditional probability distribution functions to relate daily precipitation sequences and the corresponding subdaily fragments from at-site records or other stations such as neighboring or more correlated ones [80,81].…”

Spatiotemporal variability of extreme precipitation in east of northwest China and associated large-scale circulation factors

“…It could lead to a series of catastrophic consequences in ecosystems, agriculture, and human health (WMO, 2021). Moreover, climate change profoundly affects the frequency and intensity of extreme climate events (Ahsan et al 2022;Gudmundsson et al 2021;Rafatnejad et al 2022). In recent years, heat, flood, and drought records have been repeatedly broken in several countries (Rastogi et al 2020;Schiermeier, 2021).…”

Estimation of future extreme rainfall in Barcelona (Spain) under monofractal hypothesis

“…From a more theoretical viewpoint, synthetic hyetographs can also be obtained from stochastic processes of rainfall disaggregation. For instance, the method of fragments is a daily‐to‐subdaily scaling that uses a nonparametric resampling approach and conditional probability distribution functions to relate daily rainfall vectors and the corresponding subdaily fragments from at‐site records or other stations such as neighbouring or more correlated ones (Li et al, 2018; Rafatnejad et al, 2022).…”